April brought a shift in the conversation around growth. For a long time, scaling customer support followed a familiar and largely unquestioned pattern. More customers meant more tickets, more complexity, and that ultimately meant more people. So, growth and cost essentially moved side by side.
It was inefficient, but it was predictable, and in an industry built around large offices and long leases, predictability was a key factor in client discussions.
However, in 2026, that long-established model has broken apart. Not because AI has suddenly made human support obsolete — it hasn't, and the people claiming otherwise tend to have something to sell — but because the assumptions underneath the old model no longer hold.
The world is more digitally connected than ever, talent is no longer restricted to cities, and clients now need something different: teams with time zone availability, cultural compatibility, fluent in both your brand's and your customer's language, and the sound judgment and empathy that can resolve complex issues satisfactorily with fewer escalations.
That is what April's conversations kept coming back to:
How you build your operations function matters just as much as how fast you grow.
And for the companies willing to be honest about what AI can and cannot do, there is a real and growing competitive advantage on the table.
What’s worth your attention this month?
1. AI is not the reason for the layoffs, and confusing the two is a mistake the CX industry can't afford to make
Salesforce CEO Marc Benioff made an argument this month that deserves more attention than it received. The wave of tech layoffs attributed to AI, he argued, is largely covering for cost decisions and infrastructure commitments that have little to do with automation. For customer experience teams trying to read the signals, the distinction is important. At Benioff's own company, AI resolves around half of incoming support queries, but experienced support teams are still core to the rest, and the increasingly common two-way handoffs between AI tech and human agents are becoming a key part of the value creation chain. Agents handling routine tier-one queries face real pressure, but those capable of contextual judgment and relationship-building are becoming more indispensable than ever.
2. What happens when building custom CX tools goes from a six-month project to a two-hour afternoon
A contact center veteran built three working customer service tools — a sales profiler, a chat simulation trainer, and a contact centre digital twin — in a single session using AI coding tools. The results were impressive, but the real insight was more subtle: as the cost of building custom software collapses, the real problem shifts upstream to governance. Unmanaged tools flooding an operation create complexity and risk that outpaces the value they deliver. For CX leaders, the opportunity is real, but so is the need for a framework around how new tooling gets introduced, tested, and maintained.
What do we think about it?
1. The overhead that used to make global expansion slow and expensive is what a remote-first model was designed to remove
In the traditional outsourcing model, expanding into a new market meant offices, equipment, local administration, and a management layer before a single customer query was answered. That overhead made the economics of smaller, faster, more specialized operations almost impossible to justify. The companies that figure out how to remove that cost can reinvest it where it drives outcomes: in people, training and technology.
This was the founding logic of Otonomee, and it’s held up in practice. When a client needs to ramp up support in a new region, the recruitment, onboarding, and technology infrastructure are already in place. As Hilary O’Shea put it on the ThinkBusiness podcast this month, that speed of response is a competitive advantage for clients who need to move quickly.
"We can ramp up automatically to support the needs of our clients wherever they are. We don't need to take out a lease, hire a country head, or get a team in place before we start. That gives us a competitive advantage — and it gives our clients a competitive advantage to deliver quickly." Hilary O'Shea, Co-founder
Listen to the ThinkBusiness podcast
Where we’ve been
1. Austin, Texas: Intercom Fin.ai Blueprint and SaaStock USA
Our Business Development Director, Kevin Mitchell spent the week in rooms full of operators, founders, and CX leaders, and the theme that ran through both events was consistent: the companies leading the next wave of AI-driven growth are not the ones with the biggest models, but the ones with the deepest domain expertise, applying AI to specific industry challenges in ways that general-purpose tools simply can't replicate.
For support specifically, the clearest signal was that AI is helping companies break the assumption that headcount must grow linearly with customer demand, and shifting the focus for human agents toward complexity, proactive engagement, and long-term relationships, and that is a shift Otonomee has been building toward since day one.
Closing thoughts
April reinforced a question we think more companies should be sitting with: not "how do we handle more?" but "how do we stay in control of the experience as we grow?"
Those are different questions, and they lead to different decisions. While the first is an operations problem, the second is a strategic one, and increasingly, the companies coming to us are thinking about it in strategic terms, on how support reflects the brand, how it scales without diluting quality, and how AI fits into an operation where human judgment still closes the loop on the moments that matter.
As Hilary put it on the ThinkBusiness podcast this month:
"The implementation of AI within businesses is always going to be a challenge for customers, so we can partner and aid in that respect. Our team members are qualified to solve the complex, not the transactional, which, of course, is easily removed by AI. So, the incorporation of Otonomee five years ago was timely — we have been perched on the precipice of being ready and now we have a critical mass."
If you are thinking about how your support model needs to evolve, whether that is scaling into new markets, integrating AI, or simply protecting quality as demand increases, it is a conversation worth having.
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